Dynamic constraint-satisfaction models and figurative language

31 May 2024
Room G1

Dynamic constraint-satisfaction models and figurative language

Understanding figurative language, such as irony and metaphor, has long intrigued researchers in psycholinguistics and cognitive science. Parallel constraint-satisfaction models propose that individuals interpret meaning probabilistically, constructing the most fitting interpretation from available information metaphor (Pexman, Ferretti, and Katz, 2000; Katz, 2005; Pexman, 2008). These models can be instantiated in a connectionist neural network, with each interconnected unit representing a potential solution for the comprehension problem. The model processes the information by adjusting the activation levels of the units via a relaxation mechanism until the network reaches a stable state (Pexman, 2008).

Despite their utility, constraint-satisfaction models face criticism for inadequately addressing how different forces operate over varying time scales and interact to produce emergent figurative behaviours (Gibbs and Colston, 2012). Dynamic systems offer a potential solution. They are able to automatically reconfigure their phase space, and therefore the strength and positioning of their attractors, in response to changes in their operational environment.

This contribution aims to integrate dynamic and constraint-satisfaction models to explain how forces operating on different time scales, combined with probabilistic meaning analysis, dynamically influence the conformation of the cognitive phase space.

Drawing on examples and literature, this presentation will explore how heterogeneous factors impact a system in continuous search for a stable state, i.e., a coherent interpretation. By integrating these theoretical frameworks, the contribution aims to provide a more comprehensive account of figurative language comprehension, highlighting the interplay between stability and flexibility in cognitive processes.



Gibbs, R. W., & Colston, H. L. (2012). Interpreting figurative meaning. Cam- bridge University Press.

Katz, A. N. (2005). Discourse and sociocultural factors in understanding non-literal language. In Figurative Language Comprehension (pp. 183-207). Routledge.

Pexman, P. M. (2008). It’s fascinating research: The cognition of verbal irony. Current Directions in Psychological Science, 17 (4), 286-290.

Pexman, P. M., Ferretti, T. R., & Katz, A. N. (2000). Discourse factors that influence online reading of metaphor and irony. Discourse Processes, 29 (3), 201-222.